scholarly journals Population-Based Linkage of Big Data in Dental Research

2018 ◽  
Vol 15 (11) ◽  
pp. 2357 ◽  
Author(s):  
Tim Joda ◽  
Tuomas Waltimo ◽  
Christiane Pauli-Magnus ◽  
Nicole Probst-Hensch ◽  
Nicola Zitzmann
Keyword(s):  
Clinical Trials ◽  
Big Data ◽  
Healthcare Services ◽  
Population Based ◽  
Services Research ◽  
Research Education ◽  
Data Anonymization ◽  
Dental Research ◽  
Epidemiological Surveys ◽  
Patient Consent

Population-based linkage of patient-level information opens new strategies for dental research to identify unknown correlations of diseases, prognostic factors, novel treatment concepts and evaluate healthcare systems. As clinical trials have become more complex and inefficient, register-based controlled (clinical) trials (RC(C)T) are a promising approach in dental research. RC(C)Ts provide comprehensive information on hard-to-reach populations, allow observations with minimal loss to follow-up, but require large sample sizes with generating high level of external validity. Collecting data is only valuable if this is done systematically according to harmonized and inter-linkable standards involving a universally accepted general patient consent. Secure data anonymization is crucial, but potential re-identification of individuals poses several challenges. Population-based linkage of big data is a game changer for epidemiological surveys in Public Health and will play a predominant role in future dental research by influencing healthcare services, research, education, biotechnology, insurance, social policy and governmental affairs.

scholarly journals Use of the CANHEART ‘big data’ registry to conduct a large randomized registry clinical trial to improve lipid management in Ontario, Canada

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Anam Khan ◽  
Jing Jia ◽  
Anna Chu ◽  
Jacob Udell ◽  
Michael Farkouh ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Big Data ◽  
Cardiovascular Risk ◽  
Population Based ◽  
Eligibility Criterion ◽  
Lipid Management ◽  
Data Registry ◽  
Cluster Randomized ◽  
Statin Use

IntroductionCreation of registries using linked population-based databases could potentially be used to conduct large registry-based clinical trials. As part of the CANHEART-Strategy for Patient-Oriented Research (SPOR) innovative clinical trials initiative, we explored the practicality of using the linked CANHEART registry to conduct a cluster-randomized trial aimed at improving lipid management. Objectives and ApproachThe CANHEART registry (www.canheart.ca) was created through the linkage of 19 population-based health databases in Ontario, Canada, providing individual-level socio-demographic, geographic, hospitalization, disease testing/screening, mortality, prescription medication, and behavior/lifestyle information. Using CANHEART defined eligibility criterion, small and medium-sized, high cardiovascular-risk health regions (defined as having acute myocardial infarction, stroke or cardiovascular death rates greater than the Ontario average) are being randomly allocated to receive either the intervention (availability of a lipid management ‘toolbox’) or standard care. Cohort linkages to additional years of data will occur regularly over the 3-year trial to ascertain the primary outcome of appropriate statin prescribing rates.   \section*{Results} Record linkage enabled us to determine baseline characteristics of 835,345 patients aged 40-75 as of January 2016, being treated in the 28 study-eligible regions by 2,012 family physicians. Preceding the study, the baseline statin use rate was 35.7\% (in 66-75 year olds) across these regions and the cardiovascular event rate ranged from 3.78-5.64 events/1000 person-years. A randomization procedure yielded 14 regions in both the intervention and control arms which did not differ significantly in socio-demographic characteristics, traditional cardiovascular risk factors, disease history, prevalence of statin use, or access to healthcare indicators. Working groups have been established to operationalize the lipid management tools that will be made available in the intervention regions. Analysis of newly linked participant data will permit outcome ascertainment at trial completion.   \section*{Conclusion/Implications} Our work demonstrates the feasibility of using the CANHEART ‘big data’ registry to conduct a large, cluster-randomized clinical trial aimed at improving lipid management, without requiring any primary data collection. Broader use of this methodology has the potential to change the existing paradigm for conducting pragmatic clinical trial research.

Big Data Privacy Preservation Using Two Phase Top-Down Specialization Algorithm with Multidimensional Map Reduce Framework on Hadoop

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Shalin Eliabeth S. ◽  
Sarju S.
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Experimental Result ◽  
Map Reduce ◽  
Distributed Environment ◽  
Top Down ◽  
Two Phase ◽  
Data Anonymization ◽  
Big Data Privacy

Big data privacy preservation is one of the most disturbed issues in current industry. Sometimes the data privacy problems never identified when input data is published on cloud environment. Data privacy preservation in hadoop deals in hiding and publishing input dataset to the distributed environment. In this paper investigate the problem of big data anonymization for privacy preservation from the perspectives of scalability and time factor etc. At present, many cloud applications with big data anonymization faces the same kind of problems. For recovering this kind of problems, here introduced a data anonymization algorithm called Two Phase Top-Down Specialization (TPTDS) algorithm that is implemented in hadoop. For the data anonymization-45,222 records of adults information with 15 attribute values was taken as the input big data. With the help of multidimensional anonymization in map reduce framework, here implemented proposed Two-Phase Top-Down Specialization anonymization algorithm in hadoop and it will increases the efficiency on the big data processing system. By conducting experiment in both one dimensional and multidimensional map reduce framework with Two Phase Top-Down Specialization algorithm on hadoop, the better result shown in multidimensional anonymization on input adult dataset. Data sets is generalized in a top-down manner and the better result was shown in multidimensional map reduce framework by the better IGPL values generated by the algorithm. The anonymization was performed with specialization operation on taxonomy tree. The experiment shows that the solutions improves the IGPL values, anonymity parameter and decreases the execution time of big data privacy preservation by compared to the existing algorithm. This experimental result will leads to great application to the distributed environment.

scholarly journals Omega-3 Supplementation and Heart Disease: A Population-Based Diet by Gene Analysis of Clinical Trial Outcomes

Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2154
Author(s):  
Maria Luz Fernandez ◽  
Sarah A. Blomquist ◽  
Brian Hallmark ◽  
Floyd H. Chilton
Keyword(s):  
Clinical Trials ◽  
Heart Disease ◽  
Fatty Acid Desaturase ◽  
Interaction Model ◽  
Dietary Exposure ◽  
Population Based ◽  
Biologically Active ◽  
Omega 3 ◽  
Dietary Pufa ◽  
Pufa Supplementation

Omega-3 (n-3) polyunsaturated fatty acids (PUFA) and their metabolites have long been recognized to protect against inflammation-related diseases including heart disease. Recent reports present conflicting evidence on the effects of n-3 PUFAs on major cardiovascular events including death. While some studies document that n-3 PUFA supplementation reduces the risk for heart disease, others report no beneficial effects on heart disease composite primary outcomes. Much of this heterogeneity may be related to the genetic variation in different individuals/populations that alters their capacity to synthesize biologically active n-3 and omega 6 (n-6) PUFAs and metabolites from their 18 carbon dietary precursors, linoleic acid (LA, 18:2 n-6) and alpha-linolenic (ALA, 18:3, n-3). Here, we discuss the role of a FADS gene-by-dietary PUFA interaction model that takes into consideration dietary exposure, including the intake of LA and ALA, n-3 PUFAs, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in determining the efficacy of n-3 PUFA supplementation. We also review recent clinical trials with n-3 PUFA supplementation and coronary heart disease in the context of what is known about fatty acid desaturase (FADS) gene-by-dietary PUFA interactions. Given the dramatic differences in the frequencies of FADS variants that impact the efficiency of n-3 and n-6 PUFA biosynthesis, and their downstream signaling products among global and admixture populations, we conclude that large clinical trials utilizing “one size fits all” n-3 PUFA supplementation approaches are unlikely to show effectiveness. However, evidence discussed in this review suggests that n-3 PUFA supplementation may represent an important opportunity where precision interventions can be focused on those populations that will benefit the most from n-3 PUFA supplementation.

scholarly journals Increasing the Power of Polyphenols through Nanoencapsulation for Adjuvant Therapy against Cardiovascular Diseases

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4621
Author(s):  
Lucileno Rodrigues Trindade ◽  
Davi Vieira Teixeira da da Silva ◽  
Diego dos Santos Baião ◽  
Vania Margaret Flosi Paschoalin
Keyword(s):  
Clinical Trials ◽  
Cardiovascular Diseases ◽  
Adjuvant Therapy ◽  
Vascular Diseases ◽  
Ppar Γ ◽  
Epidemiological Surveys ◽  
Genes Encoding ◽  
And Oxidative Stress ◽  
Gradual Release ◽  
Inflammatory Action

Polyphenols play a therapeutic role in vascular diseases, acting in inherent illness-associate conditions such as inflammation, diabetes, dyslipidemia, hypertension, and oxidative stress, as demonstrated by clinical trials and epidemiological surveys. The main polyphenol cardioprotective mechanisms rely on increased nitric oxide, decreased asymmetric dimethylarginine levels, upregulation of genes encoding antioxidant enzymes via the Nrf2-ARE pathway and anti-inflammatory action through the redox-sensitive transcription factor NF-κB and PPAR-γ receptor. However, poor polyphenol bioavailability and extensive metabolization restrict their applicability. Polyphenols carried by nanoparticles circumvent these limitations providing controlled release and better solubility, chemical protection, and target achievement. Nano-encapsulate polyphenols loaded in food grade polymers and lipids appear to be safe, gaining resistance in the enteric route for intestinal absorption, in which the mucoadhesiveness ensures their increased uptake, achieving high systemic levels in non-metabolized forms. Nano-capsules confer a gradual release to these compounds, as well as longer half-lives and cell and whole organism permanence, reinforcing their effectiveness, as demonstrated in pre-clinical trials, enabling their application as an adjuvant therapy against cardiovascular diseases. Polyphenol entrapment in nanoparticles should be encouraged in nutraceutical manufacturing for the fortification of foods and beverages. This study discusses pre-clinical trials evaluating how nano-encapsulate polyphenols following oral administration can aid in cardiovascular performance.

Big Data and Big Data Analytics for Improved Healthcare Service and Management

2020 ◽  
Vol 8 (1) ◽  
pp. 13-51
Author(s):  
Pijush Kanti Dutta Pramanik ◽  
Saurabh Pal ◽  
Moutan Mukhopadhyay
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Healthcare Sector ◽  
Future Market ◽  
Data Generation ◽  
Related Data ◽  
Healthcare Data ◽  
Different Types

Like other fields, the healthcare sector has also been greatly impacted by big data. A huge volume of healthcare data and other related data are being continually generated from diverse sources. Tapping and analysing these data, suitably, would open up new avenues and opportunities for healthcare services. In view of that, this paper aims to present a systematic overview of big data and big data analytics, applicable to modern-day healthcare. Acknowledging the massive upsurge in healthcare data generation, various ‘V's, specific to healthcare big data, are identified. Different types of data analytics, applicable to healthcare, are discussed. Along with presenting the technological backbone of healthcare big data and analytics, the advantages and challenges of healthcare big data are meticulously explained. A brief report on the present and future market of healthcare big data and analytics is also presented. Besides, several applications and use cases are discussed with sufficient details.

scholarly journals The European Multicentre Bronchiectasis Audit and Research Collaboration (EMBARC): experiences from a successful ERS Clinical Research Collaboration

Breathe ◽  
2017 ◽  
Vol 13 (3) ◽  
pp. 180-192 ◽  
Author(s):  
James D. Chalmers ◽  
Megan Crichton ◽  
Pieter C. Goeminne ◽  
Michael R. Loebinger ◽  
Charles Haworth ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Clinical Research ◽  
Research Collaboration ◽  
Clinical Care ◽  
Research Priorities ◽  
Chronic Obstructive ◽  
List Type ◽  
European Respiratory Society ◽  
Obstructive Pulmonary Disease ◽  
Research Education

In contrast to airway diseases like chronic obstructive pulmonary disease or asthma, and rare diseases such as cystic fibrosis, there has been little research and few clinical trials in bronchiectasis. Guidelines are primarily based on expert opinion and treatment is challenging because of the heterogeneous nature of the disease.In an effort to address decades of underinvestment in bronchiectasis research, education and clinical care, the European Multicentre Bronchiectasis Audit and Research Collaboration (EMBARC) was established in 2012 as a collaborative pan-European network to bring together bronchiectasis researchers. The European Respiratory Society officially funded EMBARC in 2013 as a Clinical Research Collaboration, providing support and infrastructure to allow the project to grow.EMBARC has now established an international bronchiectasis registry that is active in more than 30 countries both within and outside Europe. Beyond the registry, the network participates in designing and facilitating clinical trials, has set international research priorities, promotes education and has participated in producing the first international bronchiectasis guidelines. This manuscript article the development, structure and achievements of EMBARC from 2012 to 2017.Educational aimsTo understand the role of Clinical Research Collaborations as the major way in which the European Respiratory Society can stimulate clinical research in different disease areasTo understand some of the key features of successful disease registriesTo review key epidemiological, clinical and translational studies of bronchiectasis contributed by the European Multicentre Bronchiectasis Audit and Research Collaboration (EMBARC) project in the past 5 yearsTo understand the key research priorities identified by EMBARC for the next 5 years

scholarly journals A Healthy Sense of Trust

2017 ◽  
Vol 2 (Suppl. 1) ◽  
pp. 1-10
Author(s):  
Denis Horgan
Keyword(s):  
European Union ◽  
Clinical Trials ◽  
Big Data ◽  
Data Protection ◽  
Fast Moving ◽  
Ethical Issues ◽  
Personalised Medicine ◽  
Drug Pricing ◽  
The Right ◽  
The Eu

In the fast-moving arena of modern healthcare with its cutting-edge science it is already, and will become more, vital that stakeholders collaborate openly and effectively. Transparency, especially on drug pricing, is of paramount importance. There is also a need to ensure that regulations and legislation covering, for example the new, smaller clinical trials required to make personalised medicine work effectively, and the huge practical and ethical issues surrounding Big Data and data protection, are common, understood and enforced across the EU. With more integration, collaboration, dialogue and increased trust among each and every one in the field, stakeholders can help mould the right frameworks, in the right place, at the right time. Once achieved, this will allow us all to work more quickly and more effectively towards creating a healthier - and thus wealthier - European Union.

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